Announcements

Prof. Emmanuel Lesaffre of the Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), Catholic University of Leuven, Belgium, presented this intensive five-day course at Stellenbosch, under the auspices of SACEMA, in association with the Department of Statistics and Actuarial Science, University of Stellenbosch. The course took place from 24-28 October 2016 at the Stellenbosch Institute for Advanced Study (STIAS), adjacent to SACEMA.

For full announcement, including target audience and pre-requisites, clickhere

Course summary:

Many statistical practitioners make use of the Bayesian approach because it allows analyses on highly structured data. An important class of models involves the analysis of follow-up studies, i.e. longitudinal-, survival studies or a combination of the two. We will illustrate the Bayesian approach for the analysis of such data, by means of examples, and focus on the analysis of longitudinal studies. For instance, Bayesian implementations will be illustrated on (generalized and non-linear) linear mixed models with non-standard distributions for the random parts, growth curve models, pharmaco-kinetic models, multivariate mixed models, joint mixed models of several random variables, longitudinal models with smooth subject-specific evolutions, longitudinal models with informative measurement times, etc. Finally, we will look at joint modeling of the survival and longitudinal process. Examples will be analysed using WinBUGS/OpenBUGS/JAGS and R-versions of them, but also dedicated R-software.

Emmanuel Lesaffre is Professor of Biostatistics at L-Biostat, K.U.Leuven, Leuven, Belgium. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval censored data, misclassification issues and clinical trials. He has written more than 350 papers in peer-reviewed statistical and medical journals. He is the founding chair of the Statistical Modelling Society, past-president of the International Society for Clinical Biostatistics and fellow of ISI and ASA. He has (co-authored six books, including that on Bayesian Biostatistics (2012) recommended for the course.

Prof Wim Delva (SACEMA, Ghent University, Hasselt University and KU Leuven) and Dr Lander Willem (Antwerp University) presented an intensive five-day course on Individual-based modelling in epidemiology, organised by SACEMA. The course took place on 27-31 March 2017, at the Stellenbosch Institute for Advanced Study (STIAS) next to SACEMA.

Course Overview

Individual-based models (IBMs), also frequently referred to as agent-based models, are a relatively new class of models that can be used to gain insight into the population dynamics of complex systems that emerge from the characteristics and behaviours of individuals in the population. This course aims to give participants the skills to design, implement, and analyse IBMs. First, we will introduce the fundamentals of modelling, as well as a popular, open-access platform for building IBMs (RNetLogo). Next, several key modelling concepts will be discussed, including:

Deciding on appropriate structure and complexity of the model

Developing rules for the actions of individual

Analysing the emerging model dynamics

Fitting the model to empirical data

Validating model inputs and outputs

Each of these concepts will be illustrated with hands-on examples that participants can run on their own laptops. In the second half of the course, two “state-of-the-art” individual-based models will be explained, run and analysed in detail. They will serve as examples of full-blown implementations of IBMs, intended to address contemporary research questions. Participants will be encouraged to share and discuss the development and fine-tuning of their own ongoing IBM-based modelling work.

The emphasis of this course will be on the basic concepts behind IBMs and on applying these in simple “toy models”, implemented with RNetLogo. The emphasis will not be on the actual programming of IBMs but rather on the process of designing, testing and analysing IBMs to address complex questions in epidemiology.

Target Audience

Post-graduate students and health science professionals whose work potentially involves the design and/or use of IBMs in epidemiology.

Ideally, participants should have used R previously for data analysis and simple programming (e.g. writing your own function). However, this is not an absolute prerequisite. R newbies will be asked to work through selected R tutorials before arriving at the course.

Lecturers

A medical doctor and epidemiologist, Wim Delva has a joint research appointment at SACEMA (Stellenbosch University, South Africa) as well as Hasselt University, Ghent University and KU Leuven in Belgium. He is interested in the application of the statistical, epidemiological and mathematical modelling techniques to describe and analyse the behavioural and biological processes underlying HIV epidemics in sub-Saharan Africa and Europe. His current research centres around the inference of sexual network structure, using phylogenetic tree data and behavioural survey data. Other ongoing research projects seek to explore the role of age-mixing patterns and heritability of HIV set point viral load in HIV transmission dynamics, as well as the impact of biomedical and behavioural interventions on HIV incidence.

Lander Willem (MSc Bio-engineering, interdisciplinary PhD Medical Sciences & Sciences) holds a post-doc position at the University of Antwerp. His research targets agent-based modeling in the field of infectious disease transmission, with a particular focus on model exploration, parameter estimation and social contact patterns. In the philosophy of engaging in interdisciplinary research, he is involved in many projects benefiting from his disease modeling and computational skills.

The SACEMA and the CEPHIA consortium have released a new R package to support the calibration of recent infection tests (including HIV "incidence assays"). Critical parameters that can be estimated with these tools include Mean Duration of Recent Infection (MDRI) and, in later releases, False Recent Rates.

This is the first official release, in what is hoped will become a wide ranging community effort to streamline and standardise the characterisation of recent infection tests.

The package is being maintained on GitHub, with a standard GPL licence, and can be found here.

SACEMA invites applications for bursaries to study towards Masters or PhD degrees, registered at any South African university and supervised by a SACEMA-affiliated or approved supervisor, in fields relating to epidemiological modelling and biostatistics.

External Bursary Application Form (whether for Masters or PhD) to be completed online

Instructions and Checklist for filling in the Application Form

The required supporting documents to be uploaded with the form are listed in the Instructions and Checklist. The instructionsalso give guidance for commissioning an academic reference letter to be sent SEPARATELY by the referee before the application deadline.